code: def test_convert_metric_value_to_float():
      torch_tensor_val = torch.rand(1)
      assert convert_metric_value_to_float_if_possible(
          torch_tensor_val
      ) == float(torch_tensor_val[0])
  
file_path: mlflow/tests/pytorch/test_pytorch_metric_value_conversion_utils.py
imports: import pytest
  import torch
  import mlflow
  from mlflow import tracking
  from mlflow.exceptions import INVALID_PARAMETER_VALUE, ErrorCode, MlflowException
  from mlflow.tracking.fluent import start_run
  from mlflow.tracking.metric_value_conversion_utils import convert_metric_value_to_float_if_possible
label_desc: Use image node_id 2 for calling a global function with example usage: test_convert_metric_value_to_float() without return types